Tracking turbulence for wind-driven halo removal using MagAO-X pyramid wavefront sensor images
Abstract
The wind-driven halo (WDH) is a persistent, low spatial frequency noise artifact that arises due to the servo-lag error inherent to all adaptive optics (AO) instruments. Spatial filtering may be employed to overcome this artifact, however, filtering out the WDH while simultaneously preserving signal from an extended astrophysical object of interest is exceptionally challenging. Additionally, since the WDH changes in intensity and position angle through an observation, data-driven algorithms (e.g., KLIP) that are commonly used to subtract the starlight need to be overly-aggressive to remove both the static and dynamic noise components. Since wavefront sensors (WFSs) continuously track the closed-loop residual wavefront error, WFS telemetry presents the ideal resource for combating this type of noise artifact through postprocessing. Using archival WFS telemetry from MagAO-X, which is the "extreme" AO instrument for the 6.5-meter Magellan-Clay telescope, we demonstrate a novel workflow for WDH reconstruction and removal in individual coronagraphic science images. MagAO-X is equipped with a pyramid WFS capable of recording wavefront telemetry at a high-cadence which is saved during data acquisition. Given this, we detail how our WFS data processing pipeline, windsoCC, cross-correlates the recorded closed-loop wavefront to measure the wind vectors of several turbulent layers of the atmosphere above Las Campanas Observatory. We then make use of the wind parameters learned through windsoCC to reconstruct the WDH footprint by leveraging a parametric model. Notably, we demonstrate a dramatic improvement in object recovery using on-sky MagAO-X images of the disk around HR 4796A at visible wavelengths.
Related
- The infrared unmodulated pyramid wavefront sensor: simulations, lab and on sky
- Performance Comparison of the Nonlinear Curvature and Shack-Hartmann Wavefront Sensors in Strong Turbulence
- Dust-driven vertical shear instability in an isothermal shearing box. I. Turbulence and gas dynamics without dust feedback
- Primordial turbulence from inflation: a new inflaton-driven turbulent regime
- Exponential Growth of Turbulent Cross Helicity in Shear-Flow-Driven Turbulence
BibTeX
@misc{kueny2026tracking,
title = {{Tracking turbulence for wind-driven halo removal using MagAO-X pyramid wavefront sensor images}},
author = {Jay K. Kueny and Jared R. Males and Alycia J. Weinberger and Laird M. Close and Joseph D. Long and Joshua Liberman and Sebastiaan Haffert and Eden McEwen and Maggie Y. Kautz and Olivier Guyon and Logan Pearce and Parker T. Johnson and Katie Twitchell and Jialin Li and Alex Hedglen and Avalon Gower and Warren Foster and Jhen Lumbres and Lauren Schatz},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.06873},
eprint = {2611.06873},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.06873},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Tracking turbulence for wind-driven halo removal using MagAO-X pyramid wavefront sensor images
AU - Jay K. Kueny
AU - Jared R. Males
AU - Alycia J. Weinberger
AU - Laird M. Close
AU - Joseph D. Long
AU - Joshua Liberman
AU - Sebastiaan Haffert
AU - Eden McEwen
AU - Maggie Y. Kautz
AU - Olivier Guyon
AU - Logan Pearce
AU - Parker T. Johnson
AU - Katie Twitchell
AU - Jialin Li
AU - Alex Hedglen
AU - Avalon Gower
AU - Warren Foster
AU - Jhen Lumbres
AU - Lauren Schatz
PY - 2026
DA - 2026/11/04
PB - arXiv
DO - 10.48550/arxiv.2611.06873
UR - https://arxiv.org/abs/2611.06873
AB - The wind-driven halo (WDH) is a persistent, low spatial frequency noise artifact that arises due to the servo-lag error inherent to all adaptive optics (AO) instruments. Spatial filtering may be employed to overcome this artifact, however, filtering out the WDH while simultaneously preserving signal from an extended astrophysical object of interest is exceptionally challenging. Additionally, since the WDH changes in intensity and position angle through an observation, data-driven algorithms (e.g., KLIP) that are commonly used to subtract the starlight need to be overly-aggressive to remove both the static and dynamic noise components. Since wavefront sensors (WFSs) continuously track the closed-loop residual wavefront error, WFS telemetry presents the ideal resource for combating this type of noise artifact through postprocessing. Using archival WFS telemetry from MagAO-X, which is the "extreme" AO instrument for the 6.5-meter Magellan-Clay telescope, we demonstrate a novel workflow for WDH reconstruction and removal in individual coronagraphic science images. MagAO-X is equipped with a pyramid WFS capable of recording wavefront telemetry at a high-cadence which is saved during data acquisition. Given this, we detail how our WFS data processing pipeline, windsoCC, cross-correlates the recorded closed-loop wavefront to measure the wind vectors of several turbulent layers of the atmosphere above Las Campanas Observatory. We then make use of the wind parameters learned through windsoCC to reconstruct the WDH footprint by leveraging a parametric model. Notably, we demonstrate a dramatic improvement in object recovery using on-sky MagAO-X images of the disk around HR 4796A at visible wavelengths.
ER -